5 Flashcards
Why Do Startup fail
- cannot cope with high uncertainty vs. cannot plan
- just do it vs planning
9 out of 10 ventures fail
reasons why startups fail
No market need: 42%
ran out of cash: 29%
not the right team: 23%
Lean Startup principles
1-5
1 Entrepreneurs are anywhere
2 Entrepreneurship means management
3 Validated Learning
4 Build-measure-Learn
5 Innovation Accounting
Being Lean = Zero Waste
Build Measure Learn Loop
0 Idea
Step 1 Build: Hypothesis of Value & Growth
Step 2 Product: Build the MVP (Test hypotheses, target early adopters)
Step 3 Measure: Reliability ≠ vanity metrics
Step 4 Data: Split tests / cohort analyses
Step 5 Learn: Validated learning
Step 6 Idea: pivot or preserve
Minimum viable product (MVP)
- maximize validated learning for least effort
- first complete solution that contains the most basic functionalities
- leaves out additional features and design
- goal: test initial assumptions/hypotheses about the product solution
- reach the market ASAP
- generate feedback, feedback is used to improve product
- sold to early adopters
- multiple MVPs possible
Fears of early market launch
1-3
1 Legal fears
2 competition & idea theft
3 Loss of marketing & brand value
Optimization vs. pivot
Optimization
- change step by step
- optimize product
- add more features
e.g. change Logo
Pivot
- optimizations show no improvements
- change strategy
e.g. Palm handhelds —> Website
Vision
- stays the same
- even if optimization or pivot vision stays the same
e.g. Paypal: Bank of the future
Pivot
1 general
2 definition
3 signals
1
- are we on the right path?
- changing of orientation in start-up
- can be result of adaption of customer demand/feedback
- routine of pivot or preserve meetings
2 definition
- new definition of basic hypotheses
- new start up BML feedback loop
3 signals
- sinking effectiveness of MVP experiments
- feeling of product development should be more effective
Variants of Pivot
1-7
1 zoom-in (partial feature of old product becomes new product)
2 zoom-out (old product becomes part of a much larger new product “glue that isn’t sticky: post-it”)
3 customer segment (wrong customer segment, focus on new)
4 customer need (related problem being important for customer has been discovered, focus on new customer need “starbucks started as retailer for coffee, then cafe”)
5 platform (youtube as online dating website)
6 channel (delivering same product through another channel)
7 technology (achieved same solution with new technology)
Vanity Metrics
- absolute numbers
- represent the truth poorly
- e.g. number website visitors per week
Cohort Analysis
- separating the customers into segments
- looking at numbers that really matter
- what customers add value? does this number increase?
- important KPI: paying users (A, not increasing, B increasing)
-e.g. number of paying customers per week
Characteristics of Data for validated learning
- data relevant for growth model
- clear outline of cause and impact
- reports as simple as possible
- access for every involved party
- data has to be trustworthy
Process of Building Experiment for Validated Learning
1-3
1 define Leap of Faith (Hypotheses of Value & growth)
2 answer the questions
- do consumers recognize the problem you are solving?
- if there was a solution, would they buy it?
- would they buy it from you?
- can you create a solution?
3 build and sell MVP, measure success
Definition validated learning
The process of creating an empirical proof, that value-creating facts for the contemporary and future business model of the company were found.
